我正在尝试将以下代码从 MATLAB 转换为 Python 以用于 EEG 项目（部分原因是 Python 稍微便宜一些！）
希望有人能指出我正确的方向：我已经开始改变它但陷入困境：特别是试图找到等效的功能。
尝试过 scipy.org （NumPy_for_Matlab_Users 等），但我不确定我的参数是否具有正确的格式/数字）
我最初使用的是 pyserial
ser.read()
读取数据然后
ord()
将其转换为整数，但此 MATLAB 代码以另一种方式处理（'uchar'）
我的主要问题是
fopen
fread
find
repmat
整个绘图部分我对 Python 的了解更少（MatPlotLib？）
MATLAB 也倾向于以“1”开头，而 Python 使用 0：我也尝试过更改这些，但遗漏了一些我不确定的内容。
Python 是否满意用冒号分隔的整个范围
...repmat(0:2:10, .....
or not?
所以，这是 MATLAB：
% EEG data grabber and plotter
N = 256; % Required number of sample frames
% Read in a block of data from the OpenEEG board
hCom = serial('COM1','BaudRate',57600,'timeout',5);
fopen(hCom);
numBlocks = (ceil(17*N/256) + 1);
rawdata = zeros(numBlocks*256,1);
for n = 1:numBlocks
rawdata((0:255) + n*256) = fread(hCom, 256, 'uchar'); % Read data
end
fclose(hCom);
% Convert raw data into a Matlab matrix
% First find the first frame start
startIndex = find(rawdata == 165);
while(rawdata(startIndex(1) + 1) ~= 90)
startIndex = startIndex(2:end);
end
% Now extract the samples
frameStarts = (0:(N-1))'*17 + startIndex(1);
indices = 4 + repmat(frameStarts, 1, 6) + repmat(0:2:10, length(frameStarts), 1);
eegData = (rawdata(indices)*256 + rawdata(indices + 1)) - 512;
% eegData is now a N by 6 matrix, each column is a channel of sampled data
% Plot time-series data
figure(1)
subplot(2,1,1)
plot((0:255)/256,eegData(:,1:2))
xlabel('Time [s]');
ylabel('EEG data');
% Calculate FFT and plot spectra
subplot(2,1,2)
window = 0.5 - 0.5 * cos(2*pi*(0:255)/255); % Von-Hann Window
f = abs(fft(repmat(window',1,2) .* eegData(:,1:2)));
plot((0:127),f(1:128,:))
xlabel('Frequency [Hz]');
ylabel('EEG FFT');
这是我可怜的表弟的版本
import scipy
import serial #Serial Module to read serial port
from numpy import ceil,zeros #Ceil module & zeros for blank matrix
N = 256 #no of sample frames (256 = 1s)
#Reads a block of data from the serial port
ser = serial.Serial('COM18',57600,timeout=5)
scipy.fopen(ser) #MATLAB CODE: fopen(ser) is this correct????
numBlocks = (ceil(17*N/256) + 1)
rawdata = scipy.zeros(numBlocks*256,1)
for n = 1:numBlocks
rawdata((0:255) + n*256) = numpyio.fread(ser,256,'i') # read each byte as unsigned integer
end
ser.close()
#convert raw data to MATLAB matrix
#find start of frame (1st Byte always 165, 2nd always 90)
startIndex = find(rawdata == 165);
while (rawdata(startIndex(0) + 1) ~=90) #confirms 165,90 sequence
startIndex = startIndex(1:end) #uses rest of frame as data
end
#Extraction of sample values
#MATLAB CODE
frameStarts = (0: (N-1))'*17 + startIndex(1); #'#how to transpose matrix('): zip()??
indices = 4 + (numpy.tile(frameStarts, 1,6)) + (numpy.tile(0:2:10,length(frameStarts), 1);
eegData = (rawdata(indices)*256 + rawdata(indices +1)) - 512 #values are unsigned integers 0-1023 and must subtract 512 for actual value
#eeg data now N*6 Matrix each column is a channel of data
#MATLAB CODE: plot time series data (MatPlotLib?)
figure(1)
subplot (2,1,1)
plot((0:255)/256,eegData(:,1:2))
xlabel('Time [s]')
ylabel('EEG Voltage')
#fft
subplot(2,1,2)
window = 0.5 - 0.5*cos(2*pi*(0:255)/255);
f = abs(fft(repmat(window',1,2) .* eegData(:,1:2))) '#repmat=tile()? matrix transposition (')?
plot((0:127),f(1:128,:))
xlabel('Freq [Hz]')
ylabel('EEG FFT')
非常感谢所有建议！
Dave!
